Recently, with continuous development of digital image industry, various digital imaging devices (such as a digital camera, digital camcorder, notebook computer, cell phone, etc.) provided with a digital imaging sensor (such as a CCD or CMOS sensor) are rapidly developed and improved. There has been a trend to enhance image quality of the digital imaging devices, minimize the volume thereof, and lower the selling price thereof. Therefore, the digital imaging devices are more and more popular in the market. Nowadays, although many digital imaging devices provide such advanced functions as auto-focusing and auto-exposure, noise in digital images is inevitably generated while the digital images are being formed by the digital imaging devices. To solve this problem, the digital imaging devices must estimate the noise level of to-be-processed digital images, so as to generate noise level functions for guiding subsequent image processing procedures (such as noise removal, image enhancement, feature extraction, etc.), particularly the tune of specific parameters. Hence, it is important for a digital imaging device to precisely estimate the noise level of a digital image before executing subsequent image processing procedures.
Generally, a digital image formed by a digital imaging device, such as a digital photograph, has a noise level or a noise variance which varies with pixel intensity, wherein the noise level can be defined as a function of the pixel intensity, also known as a noise level function (NLFs). Thus, a noise estimation process executed by a digital imaging device is to estimate the noise level function of a digital image, in order to tune specific parameters of the digital imaging device.
With the development of digital image processing technologies, an innovative technology called “Multiresolution analysis” provides more better choices to enhance imaging quality of a digital imaging device. The multiresolution analysis includes a multiresolution transformation; such as wavelet transform, image pyramid, etc. The principle of multiresolution analysis is to disintegrate a digital image into a series of sub-images according to frequency layers of the digital image, so that each of the sub-images corresponds to information of a certain frequency layer of the digital image. Thus, when the digital imaging device executes various subsequent processing on the digital image formed by the digital imaging device, the processes can be performed on the sub-images of the different frequency layers. The multiresolution analysis is advantageous in increasing the flexibility and precision of the various subsequent processes (such as noise removal, motion estimation, feature extraction, etc.), and providing more room for development in enhancing the imaging quality of the digital imaging device.
Therefore, it is important for designers and manufacturers of various imaging devices to develop a method for estimating noise according to a multiresolution model, so that when an imaging device performs noise estimation on a digital image formed thereby, the noise estimation is performed on a sub-image in each of different frequency layers of a current digital image formed by the imaging device according to noise level functions of an imaging sensor of the imaging device in the different frequency layers under different imaging conditions, so as to obtain an optimized noise estimation result of the sub-image in each of the different frequency layers of the current digital image, thereby completely showing a noise distribution of the current digital image according to the multiresolution model, and effectively enhancing the efficiency and precision of noise estimation of the imaging device.
Therefore, in order to solve the problem that the traditional imaging device cannot precisely and efficiently estimate a noise level of a digital image, the present inventor after persistent research finally succeeded in developing a method for estimating noise according to a multiresolution model, so that an imaging device using the method of the present invention can precisely and efficiently estimate noise level functions of sub-images in different frequency layers of a digital image when the digital image is being formed by the imaging device.